Databricks

Read from and write to Databricks.

Getting Started

Prerequisites to create a Databricks based workflow. You will need

1. A source Databricks connection.

2. (optional) A list of tables OR SQL queries.

3. (optional) A destination Databricks connection.

Do not use your input Databricks connection as an output connector. This action can result in the unintended overwriting of existing data.

Create a Connection

Before creating the Databricks connection on Gretel, please ensure that the compute cluster has been started (i.e. Spark Cluster or SQL Warehouse) to ensure that validation doesn't timeout.

A databricks connection is created using the following parameters:

Connection Creation Parameters

name	Display name of your choosing used to identify your connection within Gretel.	my-databricks-connection
server_hostname	Fully qualified domain name (FQDN) used to establish connection to database server.	account_identifier.cloud.databricks.com
http_path	The http path of the cluster.	/sql/1.0/warehouses/foo
personal_access_token	Security credential to authenticate databricks account (36 characters)	dapi....
catalog	Name of catalog to connect to.	MY_CATALOG
schema	Name of schema.	MY_SCHEMA
(optional) params	Optional JDBC URL parameters that can be used for advanced configuration.	role=MY_ROLE

Create a Service Principal & Personal Access Token

In order to generate a personal access token you will first need to create a service principal, and then generate a personal access token for that service account.

Manage service principalsdatabricks

Manage service principalsdatabricks

Creating Connections

CLI

First, create a file on your local computer containing the connection credentials. This file should also include type, name , config, and credentials. The config and credentials fields should contain fields that are specific to the connection being created.

Below is an example Databricks connection:

{
    "type": "databricks",
    "name": "my-databricks-connection",
    "config": {
        "server_hostname": "account_identifier.cloud.databricks.com",
        "http_path": "/sql/1.0/warehouses/foo",
        "catalog": "MY_WAREHOUSE",
        "schema": "MY_SCHEMA",
        "params": "role=MY_ROLE"
    },
    "credentials": {
        "personal_access_token": "dapi..."
    }
}

Now that you've created the credentials file, use the CLI to create the connection

gretel connections create --project [project id] --from-file [credential_file.json]

Console

• Navigate to the Connections page using the menu item in the left sidebar.
• Click the New Connection button.

• Step 1, choose the Type for the Connection - Databricks.

• Step 2, choose the Project for your Connection.

• Step 3, fill in the credentials and select Add Connection.

Step 1, choose the Type of connection

Step 3, fill in credentials

SDK

from gretel_client import create_or_get_unique_project
from gretel_client.config import get_session_config
from gretel_client.rest_v1.api.connections_api import ConnectionsApi
from gretel_client.rest_v1.models import (
    CreateConnectionRequest,
    UpdateConnectionRequest,
)

session = get_session_config()
connection_api = session.get_v1_api(ConnectionsApi)

project = create_or_get_unique_project(name="databricks-workflow")

connection = connection_api.create_connection(
    CreateConnectionRequest(
        name="my-databricks-connection",
        project_id=project.project_guid,
        type="databricks",
        config={
            "server_hostname": "account_identifier.cloud.databricks.com",
            "http_path": "/sql/1.0/warehouses/foo",
            "catalog": "MY_WAREHOUSE",
            "schema": "MY_SCHEMA",
            "params": "role=MY_ROLE"
        },
        # note: best practice is to read in credentials from a file
        # or secret instead of directly embedding sensitive values
        # in python code.
        credentials={
            "personal_access_token": "dapi...",
        },
    )
)

Permissions

Source Connection Permissions

The Databricks source action requires enough access to read from tables and access schema metadata.

Add the following permissions to the Service Principal that was created above in order to be able to read data.

Databricks Source Permissions

Destination Connection Permissions

Ensure that the user/server principal is a part of the ownership group for the Destination catalog or schema.

The Databricks destination action requires enough permissions to write to the destination schema.

Add the following permissions to the Service Principal that was created above in order to be able to write data.

Databricks Destination Permissions